dataquieR: Data Quality in Epidemiological Research (original) (raw)

Data quality assessments guided by a 'data quality framework introduced by Schmidt and colleagues, 2021' <doi:10.1186/s12874-021-01252-7> target the data quality dimensions integrity, completeness, consistency, and accuracy. The scope of applicable functions rests on the availability of extensive metadata which can be provided in spreadsheet tables. Either standardized (e.g. as 'html5' reports) or individually tailored reports can be generated. For an introduction into the specification of corresponding metadata, please refer to the 'package website' <https://dataquality.qihs.uni-greifswald.de/VIN_Annotation_of_Metadata.html>.

Version:

2.5.1

Depends:

R (≥ 3.6.0)

Imports:

dplyr (≥ 1.0.2), emmeans, ggplot2 (≥ 3.5.0), lme4, lubridate, MASS, MultinomialCI, parallelMap, patchwork (≥ 1.3.0), R.devices, rlang, robustbase, qmrparser, utils, rio, readr, scales, withr, lifecycle, units, methods

Suggests:

openxlsx2, GGally, grDevices, jsonlite, cli, whoami, anytime, cowplot (≥ 0.9.4), digest, DT (≥ 0.23), flexdashboard, flexsiteboard, htmltools, knitr, markdown, parallel, parallelly, rJava, rmarkdown, rstudioapi, testthat (≥ 3.1.9), tibble, vdiffr, pkgload, Rdpack, callr, colorspace, plotly, ggvenn, htmlwidgets, future, processx, R6, shiny, xml2, mgcv, rvest, textutils, dbx, ggpubr, grImport2, rsvg, stringdist, rankICC, nnet, ordinal, storr, reticulate

Published:

2025-03-05

DOI:

10.32614/CRAN.package.dataquieR

Author:

University Medicine Greifswald [cph], Elisa Kasbohm [aut], Elena Salogni [aut], Joany Marino [aut], Adrian Richter [aut], Carsten Oliver Schmidt [aut], Stephan Struckmann [aut, cre], German Research Foundation (DFG SCHM 2744/3-1, SCHM 2744/9-1, SCHM 2744/3-4) [fnd], National Research Data Infrastructure for Personal Health Data: (NFDI 13/1) [fnd], European Union’s Horizon 2020 programme (euCanSHare, grant agreement No. 825903) [fnd]